Integrate the Snowflake API with the Python API

Setup the Snowflake API trigger to run a workflow which integrates with the Python API. Pipedream's integration platform allows you to integrate Snowflake and Python remarkably fast. Free for developers.

Popular Ways to Connect Snowflake with Python#

Run Python Code with Python API on New Row from Snowflake API

Snowflake + Python

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Run Python Code with Python API on Query Results from Snowflake API

Snowflake + Python

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Run Python Code with Python API on Failed Task in Schema from Snowflake API

Snowflake + Python

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Run Python Code with Python API on New Database from Snowflake API

Snowflake + Python

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Run Python Code with Python API on New Deleted Role from Snowflake API

Snowflake + Python

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Popular Snowflake and Python Triggers#

New Row from the Snowflake API

Emit new event when a row is added to a table

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New Query Results from the Snowflake API

Run a SQL query on a schedule, triggering a workflow for each row of results

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Failed Task in Schema from the Snowflake API

Emit new events when a task fails in a database schema

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New Database from the Snowflake API

Emit new event when a database is created

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New Deleted Role from the Snowflake API

Emit new event when a role is deleted

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Popular Snowflake and Python Actions#

Run Python Code with the Python API

Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.

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Insert Multiple Rows with the Snowflake API

Insert multiple rows into a table

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Insert Single Row with the Snowflake API

Insert a row into a table

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Overview of Snowflake#

Snowflake offers a cloud database and related tools to help developers create robust, secure, and scalable data warehouses. See Snowflake's Key Concepts & Architecture.

Getting Started

1. Create a user, role and warehouse in Snowflake

Snowflake recommends you create a new user, role, and warehouse when you integrate a third-party tool like Pipedream. This way, you can control permissions via the user / role, and separate Pipedream compute and costs with the warehouse. You can do this directly in the Snowflake UI.

We recommend you create a read-only account if you only need to query Snowflake. If you need to insert data into Snowflake, add permissions on the appropriate objects after you create your user.

2. Enter those details in Pipedream

Visit https://pipedream.com/accounts. Click the button to Connect an App. Enter the required Snowflake account data.

You'll only need to connect your account once in Pipedream. You can connect this account to multiple workflows to run queries against Snowflake, insert data, and more.

3. Build your first workflow

Visit https://pipedream.com/new to build your first workflow. Pipedream workflows let you connect Snowflake with 1,000+ other apps. You can trigger workflows on Snowflake queries, sending results to Slack, Google Sheets, or any app that exposes an API. Or you can accept data from another app, transform it with Python, Node.js, Go or Bash code, and insert it into Snowflake.

Learn more at Pipedream University.

Connect Snowflake#

import { promisify } from 'util'
import snowflake from 'snowflake-sdk'

export default defineComponent({
  props: {
    snowflake: {
      type: "app",
      app: "snowflake",
    }
  },
  async run({steps, $}) {
    const connection = snowflake.createConnection({
      ...this.snowflake.$auth,
      application: "PIPEDREAM_PIPEDREAM",
    })
    const connectAsync = promisify(connection.connect)
    await connectAsync()
    
    async function connExecuteAsync(options) {
      return new Promise((resolve, reject) => {
        connection.execute({
          ...options,
          complete: function(err, stmt, rows) {
            if (err) {
              reject(err)
            } else {
              resolve({stmt, rows})
            }
          }
        })
      })
    }
    
    // See https://docs.snowflake.com/en/user-guide/nodejs-driver-use.html#executing-statements
    const { rows } = await connExecuteAsync({
      sqlText: `SELECT CURRENT_TIMESTAMP()`,
    })
    return rows
  },
})

Overview of Python#

Develop, run and deploy your Python code in Pipedream workflows. Integrate seamlessly between no-code steps, with connected accounts, or integrate Data Stores and manipulate files within a workflow.

This includes installing PyPI packages, within your code without having to manage a requirements.txt file or running pip.

Below is an example of using Python to access data from the trigger of the workflow, and sharing it with subsequent workflow steps:

Connect Python#

def handler(pd: "pipedream"):
  # Reference data from previous steps
  print(pd.steps["trigger"]["context"]["id"])
  # Return data for use in future steps
  return {"foo": {"test":True}}